This story was first published in digitalhealth.net

Clinicians and engineers in Southampton have developed a microchip that could detect sight-threatening eye infections within minutes, and prevent misuse of antibiotics.
Convention testing methods can take anywhere between 48 hours and two weeks to provide results.
Working alongside ophthalmologists at University Hospital Southampton NHS Foundation Trust (UHS), experts in electronic engineering and molecular microbiology at the University of Southampton used the chip to analyse the bacteria extracted from laboratory-infected tissue samples from the eye retrieval and corneal transplant services at UHS.
They found measuring the electrical properties of single bacteria as they pass one by one between tiny electrodes at high speed an instantly identify that an infection is present and distinguish between different bacteria - something not possible using existing techniques.
A prototype device has been approved by the Health Research Authority and Research Ethics Service for patients presenting with corneal infections at Southampton General Hospital’s eye unit, with a pilot study involving 30 patients set to launch next month.
Parwez Hossain, a consultant ophthalmologist at UHS and part of the study team, said: “The cornea is only half a millimetre thick and infections can spread rapidly and destroy this structure, so timely treatment is extremely important, but we also have the added complication that treatment can be very different for each type of bacteria present.
“These findings, although currently laboratory-based, could have deep implications for the detection and treatment of corneal infections as it has the potential to reduce diagnosis time from up to two weeks to only a few minutes – and the ability to deliver the correct antibiotics immediately.”
Hywel Morgan, professor of bioelectronics at the University of Southampton, said: “Our technique is relatively simple – we just measure the electrical signals from the cells flowing one by one through the chip and this information is enough to distinguish the different microorganisms.
“It could have widespread applications, particularly given the current challenges we face in tackling overuse of antibiotics.”
This story was first published in digitalhealth.net
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